Reports: B647856-B6: The Development of Accelerated Molecular Dynamics for Complex Gas-Phase Reactive Systems

Michael R. Salazar, Union University

A suite of programs called Accelerated Molecular Dynamics with Chemistry (AMolDC) has been written, tested,
and employed in order to perform adaptive, multilevel QM/MM simulations for
complex chemical processes in the gas-phase. A paper that examines the properties of this new method was published
recently.1 The method
is formulated to give a time-dependent, multilevel representation of the total
potential that is derived from spatially-resolved quantum mechanical (QM)
regions. Ref. 1 shows that the AMolDC
method scales linearly with system size due to the fact that at a constant
temperature and pressure, the average system size will remain approximately
constant regardless of the number of atoms in the simulation.

Fig. 1 Accuracy in the interpolant as a function of underlying grid density

The last year of work has been centered on two
items: i.) continued improvement in the accuracy
of the interpolant by a new method of optimizing the interpolant and ii.) running
computational studies of AMolDC for parallelly executed QM
calculations both with and without the interpolant. Each of these is examined in turn.

Fig. 2 Computational studies of the AMolDC program on hydrated organic clusters.

Much work over the last year has continued go
into finding a general interpolation method that is both accurate and fast. In order to make the interpolation
module more accurate and have less scatter in the accuracy with increasing grid
density, a new method of optimizing the interpolant has been employed. The new method is the so-called
leave-one-out method of optimization,1-5 where the closest grid
point to the point of interpolation is used as a basis for doing 1D line
searches to solve for the optimum value of D
in:
. The
result of this effort as been a much more stable interpolation module and the
ability for the user to a priori set
up criterion for both the energy and gradient interpolation accuracy, where no
interpolation will be performed if the interpolant cannot be formulated to give
accuracy below the input thresholds.
Shown in Fig. 1 are the results of the improved interpolant for the
energy and forces of the bicyclohept-2-ene system, where the inset shows the grid
density and interpolation error on a log-log scale.

Second, AMolDC was rewritten to submit the
QM jobs in parallel and timing tests were performed. Shown in Figure 1 is a log-log plot of CPU time for various
system sizes of small condensed phase system of water, n-propanol (np),
cyclohexanol (ch), and orthoxylene (ox).
The systems varied in sizes from 1 molecule of each to 6 molecules of
each, giving system sizes from 52 atoms to 312 atoms. The parallel QM calculations were
submitted over an 18 node cluster.
Figure 1 shows the tremendous cost savings associated with performing
interpolations (symbols) over performing parallel QM calulations with no
interpolations (lines). Levels of
theory from B3LYP with cc-pVTZ basis sets to HF with 6-31G** basis sets were
used for the various groups formed in these simulations. Figure 1 also demonstrates that system
sizes of multiple hundreds of atoms may be studied with total CPU times of
about 6 hours while interpolating on DFT and HF potential and force surfaces.

Two manuscripts have been written and submitted to the
Journal of Chemical Physics. The
first manuscript is on the interpolation module, how to perform accurate and
fast interpolations for large chemical systems. The second paper is using this interpolation methodology
within AMolDC to perform computational studies of small hydrated
organic clusters. The papers were
submitted together as back-to-back publications in the same issue.